Assistance of the computer is widespread in many human endeavors, particularly since common access to the Internet, and the computer now is a prime tool for creation of new “information” and “crowd-based” solutions to problems, wherein the solution for one is obtained from the input of many users, generally provided on the Internet. However, activities such as reading, listening and viewing, related to the consumption and absorption of that information, remain largely solitary. The present invention discloses the methods and systems that utilize the effort and experience of other users for crowd-sourced, computer-assisted improvement of the outcome and experience of a consumer, reader, listener or viewer, etc.
An elementary example of such a utility is a method and system that assists a reader of a text file by providing “highlighting” by one or more prior readers of what they regarded the significant segments of the text. The reader in this example can then pay special attention to the highlighted segments of the text and generally save reading time and, if the prior reader(s) have correctly highlighted the important sections, then have a better comprehension of the key parts of the text. If the reader agrees with the significance attached to the sections highlighted by other readers, then it would provide positive reinforcement, but in any case would help the student-reader more easily climb the learning curve.
This would often be true of books and articles dealing with complex subject matter for a general audience. An article on the consequences of industrialization in emerging market countries, for instance, may have information on population dynamics and urbanization scattered across the length of the article. An expert environmentalist looking for the environmental impact of those trends may find only a few segments worth reading, but a college student studying economics may need to study much more of the article to understand the play of forces at work in the phenomenon. Looking at what the experts found valuable may orient the student in his own reading of the article, which depending on his attainment, may be more efficiently organized by the importance of the information than by starting at the beginning and linearly reading the article.
Or, in case of a reader of fictional literature, annotations by prior readers could help a reader spot sections relating to different themes, quickly and within the context of the entire book.
Such use of the marked-up material is one example of “crowd-based intelligence” in its simplest form. Prior readers of academic texts mark the important sections of the document, which leaves later readers with the advantage of more-easily identifying those and other important sections in a particular text. Some readers may choose to ignore a prior reader's notations because the new reader either disagrees with the importance of that highlight or underline, or because that reader is more concerned with another area of the text more pertinent to the particular interest of that reader at that particular time. However, regardless of that reader's interest or motivations for reading the document, the repeated marking of important sections by other readers will continually identify further areas of the document that are of interest to the readers. Continued review and marking may lead to multiple highlighting of the same section or area of the document. Multiple markings by multiple viewers will, in turn, indicate to the reader the importance of that section or area of the document for other readers for any specific purpose, and may lead to a reader more closely attempting to comprehend that section.
Other examples of crowd-based intelligence abound. For example, several websites employ it to guide a user in decision-making using recommendations for online shopping, tracking the popularity of well-known public personalities or music, or even buzzing up an article or a blog published on the internet. The previous users' views in these applications are collectively indicated by some form of indexing or depiction, often using icons such as stars.
Internet sites known as “wilds” that allow users to post and collectively edit information on a particular topic are a somewhat related example. The posted information owes its validity to the agreement and knowledge of the crowd. Experience with wilds and other web-based content integrators shows that this crowd-based method largely succeeds in providing good information.
However, while the wilds' crowd-based technologies provide collaborative development of documents by a large group of contributors actively shaping the content, a reader is left on her own for reading the document. The focus of the present invention, on the other hand, is the consumption of the content, with the help of an intelligent crowd. Furthermore, unlike other crowd-based utilities and services which provide information about the content, the methodology of the present invention breaks down the content to help with the user's actual consumption.
Several mechanical aspects of the technology employed by the present invention are known in the art, for example, highlighting portions of an article through format differentiation, including typeface, underlining or color. Writers of articles themselves or the readers may use highlighting- or underlining of portions of articles that they regard as significant for their purposes, for instance, to emphasize, reinforce or memorize the content.
However, unlike those uses of highlighting, the present invention discloses novel use of highlighting or marking-up of the file content by many users to synthesize the content into a form to actively assist the user in activities such as reading, listening, viewing of the file.
The use herein of highlighting or marking-up of an article or application data file is also distinguishably distinct from the various annotated publications, for instance, the literary, scientific, medical, legal, political and other types of periodicals or journals, where the annotations are not a direct result of “crowd-based intelligence” and are not systematically assembled from the inputs from many users.
As used in the invention disclosed in this and related applications, “crowd-based intelligence” model forms the backbone of a method and a system in which a number of reviewers are able to highlight, edit and review content materials and share their highlights, reviews and edits with other users. This method and system operate so that as more users identify important file sections, the more the later users benefit from their collective, synthesized insights.
Highlighting as used in this invention also differs significantly from the forms of web annotation in programs, such as “Google Sidewiki” and “Reframe-It,” which allow users to post comments on the content within a website. These programs run in conjunction with web browsers so that when a user accesses any web viewable page, the program can retrieve comments associated that webpage. Frequently, then the program invites or allows the user to make his or her own comments.
However, programs of this type of web annotation simply add more content to the website, making no attempt at integration of the input from the multitude of users. Thus, the intelligence of the crowd is not being utilized as fully as in the present invention.
The notion that guides and informs the present invention is the following: The true advantage of a crowd-based system is realized if the large number of user inputs is eventually combined into measurable indices of “relevance” (or similar parameters) for the user, at least in statistical terms. Without such combination, a user is forced to wade through annotated data of many individual inputs with no help to determine what is most accurate, relevant and important.
Furthermore, unlike other prevalent methods and systems, the present invention shows how crowd-sourced inputs may be combined to assist and direct the consumer of the content to the relevant and important parts of the content, thus with a view to improving the knowledge, understanding and experience of the user with regard to content consumption, whether reading or listening or viewing the content files.